نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مدیریت صنعتی، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران.

10.22105/dmor.2021.251723.1229

چکیده

به دلیل ذات و ماهیت پیچیده و چندجانبۀ تا‌ب‌آوری در زنجیره‌های تأمین، تاکنون طرحی جامع، کامل و همه‌جانبه که اجماع غالب پژوهشگران در این حوزه را دربر داشته باشد، ارائه نشده است. در راستای تلاش برای دستیابی به چنین طرحی، تحقیق حاضر با هدف تشکیل مدل جامع ارزیابی تاب‌آوری زنجیره تأمین با استفاده از رویکرد تلفیقی مبتنی بر علم‌سنجی و روش‌های مختلف هوش مصنوعی بر پایه استخراج دانش از متن انجام گردید. جامعه آماری شامل تمامی مقالات نمایه شده مرتبط با تاب‌آوری زنجیره تأمین در دو پایگاه‌ اطلاعات علمی Scopus و WOS طی سال‌های 2002 تا 2020 میلادی است. در طی انجام سه مرحله پالایش اسناد با رویکرد مرور نظام‌مند، اطلاعات علم‌سنجی و متن کامل مربوط به 346 مقاله استخراج‌ و در فرایند تجزیه‌وتحلیل مورداستفاده قرار گرفت. بهره‌گیری از رویکردی تلفیقی بر پایه علم‌سنجی و کلان‌دادۀ استخراج‌شده از پایگاه‌های اطلاعات علمی، همراه با ابزارهای هوش مصنوعی در استخراج الگوی ارزیابی تاب‌آوری زنجیره تأمین به‌عنوان جنبه نوآوری اصلی این تحقیق می‌باشد که شناخت و تحلیلی سامانمند،‌ دقیق و بدون سوگیری از مبانی نظری تحقیقات در حوزه ارزیابی تاب‌آوری زنجیره تأمین را امکان‌پذیر ساخته است. نهایتاً الگوی ارزیابی تاب‌آوری زنجیره تأمین شامل 4 ساختار اصلی و 25 ساختار فرعی از اسناد مرتبط علمی استخراج گردید.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

An integrated approach based on scientometrics and artificial intelligence for extracting the supply chain resilience assessment model

نویسندگان [English]

  • Mostafa Ziyaei Hajipirlu
  • Houshang Taghizadeh
  • Mortaza Honarmand azimi

Department of Industrial Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran

چکیده [English]

Due to the complex and multifaceted nature of supply chain resilience, hasn't yet been proposed a comprehensive, concrete, and aggregative model that includes the prevailing consensus of researchers in this field. In order to try to achieve that, the present study was conducted with the aim of forming a comprehensive model for supply chain resilience assessment using an integrated approach based on scientometrics and various artificial intelligence methods based on knowledge extraction from the text. The statistical population includes all indexed articles related to supply chain resilience from 2002 to 2020 in the two scientific databases Scopus and WOS. During the three stages of document refinement with a systematic review approach, scientometric information, and the full text of 346 articles were extracted and used in the analysis process. Utilizing an integrated approach based on the fusion of scientometrics of related metadata, and artificial intelligence tools to extraction of supply chain resilience assessment tool obtain the main innovation of this research which makes feasible establishing an evaluation model without interfering with researcher source biases. Finally, the supply chain resilience evaluation model including 4 main structures and 25 sub-structures was extracted from related scientific documents.

کلیدواژه‌ها [English]

  • Supply Chain Resilience
  • Spectral Clustering
  • Scientometrics
  • text analysis
  • Constrained Clustering
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